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[SPARK-37517][SQL] Keep consistent order of columns with user specify for v1 table #34780

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[SPARK-37517][SQL] Keep consistent order of columns with user specify for v1 table #34780

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8 changes: 6 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala
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Expand Up @@ -258,7 +258,9 @@ case class CatalogTable(
* schema of this table's partition columns
*/
def partitionSchema: StructType = {
val partitionFields = schema.takeRight(partitionColumnNames.length)
val partitionFields = partitionColumnNames.map { partCol =>
schema.find(_.name == partCol).get
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@LuciferYang LuciferYang Dec 3, 2021 •
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Is this safe? Is there any Exception of None.get here？

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@LuciferYang LuciferYang Dec 3, 2021

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Is this consistent with the result of

partitionColumnNames.flatMap { partCol =>
  schema.find(_.name == partCol)
}

?

}
assert(partitionFields.map(_.name) == partitionColumnNames)

StructType(partitionFields)
Expand All @@ -268,7 +270,9 @@ case class CatalogTable(
* schema of this table's data columns
*/
def dataSchema: StructType = {
val dataFields = schema.dropRight(partitionColumnNames.length)
val dataFields = schema.filterNot { i =>
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@LuciferYang LuciferYang Dec 3, 2021

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i is easy to associate with index. Should we change this variable name?

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@Peng-Lei Peng-Lei Dec 16, 2021

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ok. I will change it. Thank you.

partitionColumnNames.contains(i.name)
}
StructType(dataFields)
}

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2 changes: 1 addition & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
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Expand Up @@ -105,7 +105,7 @@ case class CreateDataSourceTableCommand(table: CatalogTable, ignoreIfExists: Boo

case _ =>
table.copy(
schema = dataSource.schema,
schema = table.schema.merge(dataSource.schema),
partitionColumnNames = partitionColumnNames,
// If metastore partition management for file source tables is enabled, we start off with
// partition provider hive, but no partitions in the metastore. The user has to call
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10 changes: 1 addition & 9 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
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Expand Up @@ -215,15 +215,7 @@ case class PreprocessTableCreation(sparkSession: SparkSession) extends Rule[Logi
} else {
DDLUtils.checkTableColumns(tableDesc)
val normalizedTable = normalizeCatalogTable(tableDesc.schema, tableDesc)

val partitionSchema = normalizedTable.partitionColumnNames.map { partCol =>
normalizedTable.schema.find(_.name == partCol).get
}

val reorderedSchema =
StructType(normalizedTable.schema.filterNot(partitionSchema.contains) ++ partitionSchema)

c.copy(tableDesc = normalizedTable.copy(schema = reorderedSchema))
c.copy(tableDesc = normalizedTable)
}

case create: V2CreateTablePlan if create.childrenResolved =>
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10 changes: 5 additions & 5 deletions sql/core/src/test/resources/sql-tests/results/charvarchar.sql.out
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Expand Up @@ -506,9 +506,9 @@ desc formatted char_part
struct<col_name:string,data_type:string,comment:string>
-- !query output
c1 char(5)
c2 char(2)
v1 varchar(6)
v2 varchar(2)
c2 char(2)
# Partition Information
# col_name data_type comment
v2 varchar(2)
Expand Down Expand Up @@ -540,9 +540,9 @@ desc formatted char_part
struct<col_name:string,data_type:string,comment:string>
-- !query output
c1 char(5)
c2 char(2)
v1 varchar(6)
v2 varchar(2)
c2 char(2)
# Partition Information
# col_name data_type comment
v2 varchar(2)
Expand Down Expand Up @@ -575,9 +575,9 @@ desc formatted char_part
struct<col_name:string,data_type:string,comment:string>
-- !query output
c1 char(5)
c2 char(2)
v1 varchar(6)
v2 varchar(2)
c2 char(2)
# Partition Information
# col_name data_type comment
v2 varchar(2)
Expand Down Expand Up @@ -609,9 +609,9 @@ desc formatted char_part
struct<col_name:string,data_type:string,comment:string>
-- !query output
c1 char(5)
c2 char(2)
v1 varchar(6)
v2 varchar(2)
c2 char(2)
# Partition Information
# col_name data_type comment
v2 varchar(2)
Expand Down Expand Up @@ -643,9 +643,9 @@ desc formatted char_part
struct<col_name:string,data_type:string,comment:string>
-- !query output
c1 char(5)
c2 char(2)
v1 varchar(6)
v2 varchar(2)
c2 char(2)
# Partition Information
# col_name data_type comment
v2 varchar(2)
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4 changes: 2 additions & 2 deletions sql/core/src/test/resources/sql-tests/results/show-create-table.sql.out
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Expand Up @@ -136,9 +136,9 @@ SHOW CREATE TABLE tbl
struct<createtab_stmt:string>
-- !query output
CREATE TABLE `default`.`tbl` (
`a` INT,
`b` STRING,
`c` INT,
`a` INT)
`c` INT)
USING parquet
PARTITIONED BY (a)

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21 changes: 21 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/ShowCreateTableSuite.scala
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Expand Up @@ -226,6 +226,27 @@ abstract class ShowCreateTableSuite extends QueryTest with SQLTestUtils {
}
}

test("SPARK-37517: Keep consistent columns order with user specified") {
val t = "SPARK_37517"
withTable(t) {
sql(
s"""
|CREATE TABLE $t (
| a bigint NOT NULL,
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@Peng-Lei Peng-Lei Dec 2, 2021

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I'm a little confused that the table will be created success although column a is nullable. It seems to me that partition columns should not be nullable. @cloud-fan

| b bigint NOT NULL,
| c ARRAY<INT>,
| d STRUCT<x: INT, y: ARRAY<BOOLEAN>>
|)
|USING PARQUET
|PARTITIONED BY (a)
""".stripMargin)
val expected = s"CREATE TABLE `default`.`$t` (" +
s" `a` BIGINT NOT NULL, `b` BIGINT, `c` ARRAY<INT>," +
s" `d` STRUCT<`x`: INT, `y`: ARRAY<BOOLEAN>>) USING PARQUET PARTITIONED BY (a)"
assert(getShowDDL(s"SHOW CREATE TABLE $t") == expected)
}
}

protected def getShowDDL(showCreateTableSql: String): String = {
sql(showCreateTableSql).head().getString(0).split("\n").map(_.trim).mkString(" ")
}
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